For this study, a group of 166 people handed over access to their Instagram accounts to the researchers. Out of the 166 people, 71 had already been diagnosed with depression. In total, there were more than 43,000 photos that were analysed by the study’s computer model.

The computer model inspected these pictures pixel-by-pixel for colour, metadata, and face detection and then used its analysis to predict which of the users had depression and which ones didn’t. As this was a solely picture-analysis study, no captions or comments were examined.

Analysis revealed 70% accuracy

The computer model ended up – 70% of the time – accurately identifying the users who suffered from depression. A 70% accuracy is definitely better than an average primary care doctor – who, according to previous studies, has an accuracy of about 42 to 50% when it comes to diagnosing depression.

The purpose of this study was to find out the hidden behaviour of people through their pictures. It was discovered that there was a number of trends that users with depression followed: uploading pictures that tend to be unfiltered, bluer, darker, and grayer.

In all likelihood, depressed users tend to have more comments, which suggests that family and friends are showing their support through comments, and fewer likes. If, in some cases – a filter was used – it would usually be the black-and-white lens of Inkwell.

It’s almost as if they want all the joy – also known as colours – removed from their pictures when they are feeling low. Users with depression also post photos with faces, but they were also found to upload pictures with fewer people in them, which is a sign of their socialising status.

Professor Chris Danforth, co-author of this study, expressed that they “were looking to identify what behaviours are people exhibiting potentially without them even realising. It's a proof of concept; and for the particular individuals we studied, this set of predictors works for them.”

Social media studies shed more light on mental health situations

This study has formed a part of many other studies that analyses social media to know more about its connections with mental health. These studies have looked into Twitter and social media posts to find out if there are any links to mothers with postpartum depression; or individuals showing high risks of depression.

So far, all these studies have had substantial amount of evidence that proved individuals suffering from depression lean more towards darker colours and are also reportedly less sensitive to colours as they see the world in grey. When depressed, people’s inclinations towards colour and brightness change.

Despite the fact that the findings so far can lead to a scare of privacy intrusions, it can also help those suffering from depression get the help they need. According to Danforth, these studies might also help doctors get a quicker and more accurate diagnoses if more research is done to find out more.

Nonetheless, Danforth re-iterates that this study “is not a diagnostic test at all". In fact, “We acknowledge that depression describes a general clinical status, and is frequently combined with other conditions,” he explained. MIMS